1 день назад
Senior Software Engineer (Spark Platform)
130 600 - 192 000$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Senior Software Engineer (Spark Platform): Building and operating DoorDash's large-scale Apache Spark platform for data, analytics, and ML workloads with an accent on distributed systems, runtime optimization, multi-tenant scheduling, and reliability. Focus on designing Spark-on-Kubernetes architecture, solving shuffle and scheduling challenges at scale, and setting the platform's long-term technical direction.
Location: Hybrid; must be located in San Francisco, Sunnyvale, Seattle, or New York City, or be willing to relocate to the Bay Area, Seattle, or NYC.
Salary: $130,600–$192,000, $159,800–$235,000, or $193,800–$285,000 USD annually, depending on work location and level.
Company
is a technology and delivery platform that operates large-scale data, analytics, and machine learning systems.
What you will do
- Set the multi-year technical direction for the in-house Spark-on-Kubernetes platform, including runtime, shuffle, scheduling, and reliability.
- Own distributed-systems challenges involving shuffle architecture, multi-tenant scheduling, runtime performance, and large-scale failure modes.
- Partner with the Engineering Manager on technical roadmaps, hiring, interview design, and team structure.
- Lead design reviews, mentor engineers, and raise engineering quality across the platform team.
- Represent Spark Platform in architecture forums and collaborate with Data Engineering, ML Platform, and product engineering teams.
Requirements
- 6+ years of industry experience designing and operating distributed systems at scale.
- Deep hands-on experience with Apache Spark internals, query execution, shuffle, and the executor/driver model in a platform operations context.
- Production experience operating Kubernetes workloads, including operator patterns, executor pod lifecycle, network topology, and multi-tenant failure modes.
- Experience with remote shuffle systems, big-data schedulers, or observability and SRE practices for distributed compute platforms.
- Professional experience with Scala, Java, Python, or Go, plus strong SQL skills.
- B.S., M.S., or PhD in Computer Science or equivalent; demonstrated technical leadership, mentoring, and roadmap ownership.
Nice to have
- Experience with Amazon EMR, Databricks, Celeborn, Magnet, Cosco, YuniKorn, Volcano, Kueue, or the Spark-on-Kubernetes operator.
- Familiarity with Apache Iceberg, Delta Lake, and query or SQL engines that read these formats.
Culture & Benefits
- Hybrid work environment with location-based compensation.
- Equity grant opportunities in addition to base salary.
- 401(k) with employer matching and comprehensive medical, dental, and vision coverage.
- Flexible paid time off, paid sick leave, 11 paid holidays, and 16 weeks of paid parental leave.
- Wellness, commuter, disability, life insurance, family-forming, and mental health benefits.
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